3 artificial intelligence engineer jobs at 3 companies in Rialto, CA

PromotedHiringCafe
Founding Machine Learning / AI Search Engineer
Cupertino, CA, US
$160k-$310k/yr On-SiteFull Time
HiringCafe
HiringCafe: Building a 100× better job search engine to take on Indeed and LinkedIn.
Build the ML and AI search behind HiringCafe — ranking, recommenders, retrieval, and LLM agents that surface jobs people would never find on their own.
Python, PyTorch, Elasticsearch, LLMs
1w
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Artificial Intelligence Architect (Senior or Lead)
Arlington or North Charleston or Everett or Seal Beach or El Segundo or Hazelwood or Ridley Park or Renton or Mesa
$143k-$250k/yr HybridFull Time
Boeing
BoeingNYSE: BA: Designing and manufacturing commercial aircraft and defense systems.
5+ YOE5+ years in data engineering/software development and enterprise architecture; 3+ years AI/ML and modern programming; experience with cloud platforms, databases, AI integration, and AI model development.
AWS, Google Cloud Platform, Azure, C++, Java, JavaScript, Perl, Python, Visual Basic, Deep Learning, Natural Language Processing (NLP), Computer Vision, Generative AI, LLM/RAG
2w
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Artificial Intelligence Scientist IV
Los Angeles or Irvine
$208k-$354k/yr OnsiteFull Time
Capital Group
Capital Group: Providing active investment management and research-driven financial strategies
10+ YOEMS in CS/AI/ML required (PhD preferred), 10+ years relevant experience, expertise in LLMs, generative and agentic AI (RAG, PEFT, instruction fine-tuning, prompt engineering), transformers and deep learning, publication record, ability to collaborate with engineering and mentor scientists.
Deep Neural Networks, Large Language Models (LLMs), RAG, Transformers, Agentic AI
2d
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Senior Product Manager – Artificial Intelligence
Frisco or Newport Beach or San Jose or New York or Toronto
$124k-$204k/yr HybridFull Time
McAfee
McAfee: Provides consumer cybersecurity, identity protection, and online privacy software.
Experience leading AI/ML product development including LLMs and agentic systems, designing model evals, partnering with MLOps/data engineering, establishing safety guardrails, and translating technical metrics for stakeholders; must be commutable to listed hubs.
Large Language Models (LLMs), MLOps